Senior Computer Vision Engineer - Deep Learning Salary: 70,000 to 95,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment: Permanent, full-time. Contract opportunities may also be considered. MFK Recruitment is recruiting a Senior Computer Vision Engineer for an innovative UK technology company working at the forefront of computer vision, perception and autonomy. The company develops advanced Artificial Intelligence and Machine Learning technology for defence, security and other demanding real-world environments. Its work combines machine vision, deep learning and neuroscience-inspired approaches to create AI systems that are accurate, robust and reliable. MFK Recruitment has successfully recruited four Engineers to this company over the past five years, and all four are still with the business. This speaks volumes about the culture, technical challenges and long-term opportunities available. Senior Computer Vision Engineer role You will design, develop and deploy production-grade computer vision systems using modern deep learning techniques, with a particular focus on Convolutional Neural Networks and Vision Transformers. This is a hands-on engineering role for someone comfortable working across research, software development and real-world deployment. You will help translate recent AI research into reliable products used within demanding defence and security environments. The position is predominantly office and customer-site based in West London, although some remote working will be available. Senior Computer Vision Engineer responsibilities Design, develop and optimise computer vision models using CNNs, Vision Transformers and related deep learning architectures. Develop customised neural networks, training strategies, loss functions and evaluation metrics. Implement and adapt techniques from recent AI and computer vision research. Build scalable training, validation, evaluation and inference pipelines. Optimise models for accuracy, robustness, latency and deployment across cloud and edge platforms. Translate research outputs into maintainable, production-quality software. Collaborate with Software Engineers, Researchers, Technical Leaders and customers. Contribute to architecture decisions, testing and CI/CD practices. Support the deployment of computer vision systems into customer environments. Essential experience Strong commercial experience developing deep learning solutions for computer vision. Excellent Python development skills. Commercial experience using PyTorch. TensorFlow experience will also be considered. Strong knowledge of CNNs and modern computer vision techniques. Experience designing, modifying or adapting neural network architectures. Experience with model training, validation, hyperparameter optimisation and performance evaluation. Experience implementing techniques from recent AI or computer vision research. Experience delivering reliable AI systems into production. Strong software engineering practices, including Git, testing, code reviews and CI/CD. Excellent analytical, problem-solving and communication skills. Desirable experience Vision Transformer architectures. Object detection, tracking, segmentation or pose estimation. Multi-object localisation or multi-modal perception systems. GPU optimisation, CUDA, inference acceleration or edge AI. Real-time computer vision systems. Docker, Kubernetes, Kubeflow or MLOps pipelines. Aerial, satellite or ISR imagery. Synthetic data generation, Unreal Engine or NVIDIA Omniverse. Distributed training and large-scale model optimisation. Defence, government or national security projects. An MSc or PhD in Computer Vision, Artificial Intelligence, Machine Learning, Robotics or a related subject. Security clearance Candidates must be eligible to obtain UK BPSS and Security Check clearance. Existing clearance is advantageous but is not required for every appointment. Applicants for SC clearance are normally expected to have lived in the UK for the previous five years. A shorter period of UK residency or time spent overseas will not necessarily prevent clearance, but eligibility will be assessed individually by the sponsoring authority.
01/09/2026
Full time
Senior Computer Vision Engineer - Deep Learning Salary: 70,000 to 95,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment: Permanent, full-time. Contract opportunities may also be considered. MFK Recruitment is recruiting a Senior Computer Vision Engineer for an innovative UK technology company working at the forefront of computer vision, perception and autonomy. The company develops advanced Artificial Intelligence and Machine Learning technology for defence, security and other demanding real-world environments. Its work combines machine vision, deep learning and neuroscience-inspired approaches to create AI systems that are accurate, robust and reliable. MFK Recruitment has successfully recruited four Engineers to this company over the past five years, and all four are still with the business. This speaks volumes about the culture, technical challenges and long-term opportunities available. Senior Computer Vision Engineer role You will design, develop and deploy production-grade computer vision systems using modern deep learning techniques, with a particular focus on Convolutional Neural Networks and Vision Transformers. This is a hands-on engineering role for someone comfortable working across research, software development and real-world deployment. You will help translate recent AI research into reliable products used within demanding defence and security environments. The position is predominantly office and customer-site based in West London, although some remote working will be available. Senior Computer Vision Engineer responsibilities Design, develop and optimise computer vision models using CNNs, Vision Transformers and related deep learning architectures. Develop customised neural networks, training strategies, loss functions and evaluation metrics. Implement and adapt techniques from recent AI and computer vision research. Build scalable training, validation, evaluation and inference pipelines. Optimise models for accuracy, robustness, latency and deployment across cloud and edge platforms. Translate research outputs into maintainable, production-quality software. Collaborate with Software Engineers, Researchers, Technical Leaders and customers. Contribute to architecture decisions, testing and CI/CD practices. Support the deployment of computer vision systems into customer environments. Essential experience Strong commercial experience developing deep learning solutions for computer vision. Excellent Python development skills. Commercial experience using PyTorch. TensorFlow experience will also be considered. Strong knowledge of CNNs and modern computer vision techniques. Experience designing, modifying or adapting neural network architectures. Experience with model training, validation, hyperparameter optimisation and performance evaluation. Experience implementing techniques from recent AI or computer vision research. Experience delivering reliable AI systems into production. Strong software engineering practices, including Git, testing, code reviews and CI/CD. Excellent analytical, problem-solving and communication skills. Desirable experience Vision Transformer architectures. Object detection, tracking, segmentation or pose estimation. Multi-object localisation or multi-modal perception systems. GPU optimisation, CUDA, inference acceleration or edge AI. Real-time computer vision systems. Docker, Kubernetes, Kubeflow or MLOps pipelines. Aerial, satellite or ISR imagery. Synthetic data generation, Unreal Engine or NVIDIA Omniverse. Distributed training and large-scale model optimisation. Defence, government or national security projects. An MSc or PhD in Computer Vision, Artificial Intelligence, Machine Learning, Robotics or a related subject. Security clearance Candidates must be eligible to obtain UK BPSS and Security Check clearance. Existing clearance is advantageous but is not required for every appointment. Applicants for SC clearance are normally expected to have lived in the UK for the previous five years. A shorter period of UK residency or time spent overseas will not necessarily prevent clearance, but eligibility will be assessed individually by the sponsoring authority.
Machine Learning Engineer - Spiking Neural Networks Salary: 75,000 to 100,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment: Permanent, full-time MFK Recruitment is seeking a specialist Machine Learning Engineer to help develop an engineering-grade Spiking Neural Network engine for practical machine vision applications. Our client develops advanced AI and Machine Learning technology for defence, security and other demanding operational environments. Its work combines computer vision, perception and neuroscience-inspired technology to produce accurate and robust AI systems. MFK Recruitment has successfully recruited four Engineers to this company over the past five years, and all four are still with the business. Machine Learning Engineer role You will combine current knowledge of Spiking Neural Networks with strong C++ software development skills to transform advanced research into a practical and usable product. This is a rare opportunity to apply genuine SNN experience to production software with direct operational applications. You will work alongside Researchers, Data Scientists and Engineers on SNNs, machine vision, synthetic training data and related CNN or Transformer-based projects. The position is predominantly office and customer-site based in West London, although some remote working will be available. Machine Learning Engineer responsibilities Apply your knowledge of SNNs to the development of a novel machine vision engine. Develop high-quality C++ software based on research outputs and product requirements. Use machine vision and image-analysis techniques to solve complex engineering challenges. Contribute to projects using CNNs and Transformer networks. Integrate recent Machine Learning algorithms into production software. Support synthetic training-image generation and the curation of real-world ISR imagery. Work closely with Researchers to understand and implement technical solutions. Contribute to system design, version control, testing and CI/CD pipelines. Support colleagues and customers during technical discussions and project delivery. Essential experience Current hands-on experience developing Spiking Neural Networks. Strong C++ programming and software engineering skills. Knowledge of machine vision, image analysis or computer vision. The ability to understand research outputs and transform them into reliable software. Experience developing maintainable code using version control, testing and CI/CD. Strong analytical, problem-solving and communication skills. Desirable experience CUDA and GPU programming. Python and PyTorch. CNNs, Transformers or broader deep learning architectures. Synthetic training imagery and simulation environments. ISR imagery or defence-related machine vision. Commercial software development alongside academic or research experience. An MSc, PhD or postdoctoral background involving SNNs, Computer Vision, AI or Machine Learning. Security clearance Candidates must be eligible to obtain UK BPSS and Security Check clearance. Existing security clearance would be highly advantageous. Applicants for SC clearance are normally expected to have lived in the UK for the previous five years. Applicants with a shorter UK residency history may still be considered, subject to the sponsoring authority being able to complete the required checks.
01/09/2026
Full time
Machine Learning Engineer - Spiking Neural Networks Salary: 75,000 to 100,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment: Permanent, full-time MFK Recruitment is seeking a specialist Machine Learning Engineer to help develop an engineering-grade Spiking Neural Network engine for practical machine vision applications. Our client develops advanced AI and Machine Learning technology for defence, security and other demanding operational environments. Its work combines computer vision, perception and neuroscience-inspired technology to produce accurate and robust AI systems. MFK Recruitment has successfully recruited four Engineers to this company over the past five years, and all four are still with the business. Machine Learning Engineer role You will combine current knowledge of Spiking Neural Networks with strong C++ software development skills to transform advanced research into a practical and usable product. This is a rare opportunity to apply genuine SNN experience to production software with direct operational applications. You will work alongside Researchers, Data Scientists and Engineers on SNNs, machine vision, synthetic training data and related CNN or Transformer-based projects. The position is predominantly office and customer-site based in West London, although some remote working will be available. Machine Learning Engineer responsibilities Apply your knowledge of SNNs to the development of a novel machine vision engine. Develop high-quality C++ software based on research outputs and product requirements. Use machine vision and image-analysis techniques to solve complex engineering challenges. Contribute to projects using CNNs and Transformer networks. Integrate recent Machine Learning algorithms into production software. Support synthetic training-image generation and the curation of real-world ISR imagery. Work closely with Researchers to understand and implement technical solutions. Contribute to system design, version control, testing and CI/CD pipelines. Support colleagues and customers during technical discussions and project delivery. Essential experience Current hands-on experience developing Spiking Neural Networks. Strong C++ programming and software engineering skills. Knowledge of machine vision, image analysis or computer vision. The ability to understand research outputs and transform them into reliable software. Experience developing maintainable code using version control, testing and CI/CD. Strong analytical, problem-solving and communication skills. Desirable experience CUDA and GPU programming. Python and PyTorch. CNNs, Transformers or broader deep learning architectures. Synthetic training imagery and simulation environments. ISR imagery or defence-related machine vision. Commercial software development alongside academic or research experience. An MSc, PhD or postdoctoral background involving SNNs, Computer Vision, AI or Machine Learning. Security clearance Candidates must be eligible to obtain UK BPSS and Security Check clearance. Existing security clearance would be highly advantageous. Applicants for SC clearance are normally expected to have lived in the UK for the previous five years. Applicants with a shorter UK residency history may still be considered, subject to the sponsoring authority being able to complete the required checks.
Senior Machine Learning Engineer Remote Salary 90,000- 160,000 (flexable) Hexwired Recruitment has partnered with an innovative AI technology company developing next-generation machine learning systems for real-world applications. They're looking for an experienced Machine Learning Engineer to join a small, highly technical team building production-grade AI solutions from the ground up. The Role This is a hands-on engineering position where you'll take ownership of key machine learning components throughout their entire lifecycle. You'll be responsible for designing, developing and deploying scalable ML systems that solve complex real-world problems. Your responsibilities will include: Designing and implementing production-ready machine learning systems. Owning the full ML lifecycle, from data preparation and model training through to deployment and optimisation. Translating research concepts into robust, scalable production solutions. Monitoring, debugging and improving models using production data and user feedback. Working closely with software engineers, researchers and product teams to deliver impactful features. Mentoring other engineers through technical leadership, code reviews and best practices. Building systems that balance performance, latency, reliability and scalability. Technology Python PyTorch and/or JAX GPU-based model training and inference Modern machine learning infrastructure What We're Looking For Commercial experience building and deploying machine learning models into production. Strong understanding of modern ML architectures and production challenges. Excellent software engineering skills with a focus on maintainable, production-quality code. Ability to work independently and take ownership of technical delivery. Strong problem-solving skills and a pragmatic approach to engineering. Excellent communication skills and a collaborative mindset. Apply today by contacting Hexwired Recruitment. If you are an experienced Senior Machine Learning Engineer looking for a new remote opportunity paying a market-leading salary up to 160,000. Apply today by contacting Hexwired Recruitment. For more information on this role, or any other jobs across; Embedded, C++ programming, Embedded Linux, Golang Development, FPGA, Python, Javascript, C#, Electronics, Secure Boot, Power Electronics, Digital Design, Machine Learning, Data Science or Simulation contact us today.
01/09/2026
Full time
Senior Machine Learning Engineer Remote Salary 90,000- 160,000 (flexable) Hexwired Recruitment has partnered with an innovative AI technology company developing next-generation machine learning systems for real-world applications. They're looking for an experienced Machine Learning Engineer to join a small, highly technical team building production-grade AI solutions from the ground up. The Role This is a hands-on engineering position where you'll take ownership of key machine learning components throughout their entire lifecycle. You'll be responsible for designing, developing and deploying scalable ML systems that solve complex real-world problems. Your responsibilities will include: Designing and implementing production-ready machine learning systems. Owning the full ML lifecycle, from data preparation and model training through to deployment and optimisation. Translating research concepts into robust, scalable production solutions. Monitoring, debugging and improving models using production data and user feedback. Working closely with software engineers, researchers and product teams to deliver impactful features. Mentoring other engineers through technical leadership, code reviews and best practices. Building systems that balance performance, latency, reliability and scalability. Technology Python PyTorch and/or JAX GPU-based model training and inference Modern machine learning infrastructure What We're Looking For Commercial experience building and deploying machine learning models into production. Strong understanding of modern ML architectures and production challenges. Excellent software engineering skills with a focus on maintainable, production-quality code. Ability to work independently and take ownership of technical delivery. Strong problem-solving skills and a pragmatic approach to engineering. Excellent communication skills and a collaborative mindset. Apply today by contacting Hexwired Recruitment. If you are an experienced Senior Machine Learning Engineer looking for a new remote opportunity paying a market-leading salary up to 160,000. Apply today by contacting Hexwired Recruitment. For more information on this role, or any other jobs across; Embedded, C++ programming, Embedded Linux, Golang Development, FPGA, Python, Javascript, C#, Electronics, Secure Boot, Power Electronics, Digital Design, Machine Learning, Data Science or Simulation contact us today.
Senior C++ Developer Permanent Fully Remote Negotiable Salary + Significant Equity From Oxford research to securing the connected world Nine years ago, a small UK technology team working alongside researchers at the University of Oxford set out to solve a problem most of the world didn t yet realise it had. Billions of machines were beginning to talk to each other across factories, power grids, transport systems, defence networks and smart cities. But much of that communication depended on architectures built for a different era: centralised, vulnerable and increasingly exposed. So they built something different. Today, the company holds patented cryptographic technology that enables fully decentralised, post-quantum secure interoperability between devices operating at the edge without relying on always-on central connectivity. It can operate across untrusted environments, enable real-time communication and support narrow AI across full-scale industrial systems. What started with academic research has evolved into commercially relevant security technology with the potential for global application. Now the team is growing again, and we are looking for two exceptional Senior C++ Developers who can operate where this technology really lives deep in the network stack. The Role: Where Packets Become Trust This isn't application-layer C++. It isn't framework-driven development. This is low-level, network-centric C and C++ engineering, working primarily around OSI Layers 2 and 3, where packet behaviour, routing decisions and tunnelling strategies determine whether distributed systems can communicate securely at scale. You'll design and build technology intended ultimately to operate across millions of industrial edge devices, enabling secure cloud-to-edge communication, device-to-device authentication, decentralised routing and interoperability, secure communication across potentially untrusted networks, and robust deployment and configuration for edge environments. You'll be close enough to the technology to influence how it develops shaping architecture, solving complex networking problems and contributing to security infrastructure that could eventually underpin critical systems around the world. And because this remains a relatively small, specialist engineering team, your contribution won't disappear into a huge development organisation. You'll see the impact of what you build. What the Director of Engineering Needs in This Role This is a tall order intentionally so. First and foremost, you must have genuine depth in network programming with C and C++. We're particularly interested in engineers with strong working knowledge of Layer 3 OSI protocols, low-level packet analysis and routing, OSPF, TAP/TUN devices and UDP tunnelling, UDP hole punching and STUN technologies, IPTables and packet routing strategies, code threading and multitasking, IPC and shared-memory communication, and Linux kernel-level development. You'll ideally also be comfortable with several of the following areas: compilers and static libraries, cross-compiling and porting across iOS, Android, Windows and Linux, containerised microservices using Docker and Kubernetes, CI/CD and GitLab environments, distributed cloud platforms including AWS, Azure and OVH, and development environments including VS Code, GitLab and Nexus. We don't expect one person to tick every box. What we do need is someone who can demonstrate a high level of competence in networking, packet routing and packet analysis, together with meaningful experience across at least three or four of the areas above. That networking foundation is important. Without it, the learning curve into the technology will simply be too steep. The Kind of Engineer Who Will Thrive Here You'll probably have 10+ years' experience designing, architecting and developing sophisticated C++ systems, although depth of expertise matters more than an arbitrary number. You'll be comfortable operating in Linux environments, including Debian, CentOS and embedded variants, and ideally understand symmetric and asymmetric cryptography, hashing and secure distributed systems. More importantly, you'll be someone who enjoys getting underneath a problem. Someone who wants to understand what is actually happening to the packet, rather than simply calling an abstraction several layers above it. You'll document clearly, automate where it makes sense, challenge assumptions constructively and be comfortable working in an environment where engineers are expected to think rather than simply execute tickets. Previous start-up, IoT, edge computing, GPU/AI or blockchain experience would be useful, but isn't essential. Why This Matters Nine years in, this is no longer an academic experiment. It isn't a concept. It isn't a slide deck. And it isn't another IoT start-up promising to change the world with an idea. There is patented technology, years of engineering behind it and a platform being prepared for much wider adoption. The next stage is about scale. The successful engineers won't simply be writing C++ code. They'll be helping determine how machines authenticate, communicate and establish trust across industrial systems, critical infrastructure and other highly secure environments. You'll receive a competitive base salary plus significant equity, reflecting the opportunity to join at a stage where your contribution can still materially influence both the technology and the company's future. The role is permanent and fully remote. If you're a serious low-level C++ engineer who understands packets, routing, tunnelling and network behaviour and the idea of taking technology from Oxford research roots towards global security infrastructure sounds more interesting than another conventional development role I'd like to hear from you. Edison Hill Search are operating and advertising as an Employment Agency for permanent positions and as an Employment Business for interim / contract / temporary positions. Edison Hill Search are an Equal Opportunities employer and we encourage applicants from all backgrounds.
01/09/2026
Full time
Senior C++ Developer Permanent Fully Remote Negotiable Salary + Significant Equity From Oxford research to securing the connected world Nine years ago, a small UK technology team working alongside researchers at the University of Oxford set out to solve a problem most of the world didn t yet realise it had. Billions of machines were beginning to talk to each other across factories, power grids, transport systems, defence networks and smart cities. But much of that communication depended on architectures built for a different era: centralised, vulnerable and increasingly exposed. So they built something different. Today, the company holds patented cryptographic technology that enables fully decentralised, post-quantum secure interoperability between devices operating at the edge without relying on always-on central connectivity. It can operate across untrusted environments, enable real-time communication and support narrow AI across full-scale industrial systems. What started with academic research has evolved into commercially relevant security technology with the potential for global application. Now the team is growing again, and we are looking for two exceptional Senior C++ Developers who can operate where this technology really lives deep in the network stack. The Role: Where Packets Become Trust This isn't application-layer C++. It isn't framework-driven development. This is low-level, network-centric C and C++ engineering, working primarily around OSI Layers 2 and 3, where packet behaviour, routing decisions and tunnelling strategies determine whether distributed systems can communicate securely at scale. You'll design and build technology intended ultimately to operate across millions of industrial edge devices, enabling secure cloud-to-edge communication, device-to-device authentication, decentralised routing and interoperability, secure communication across potentially untrusted networks, and robust deployment and configuration for edge environments. You'll be close enough to the technology to influence how it develops shaping architecture, solving complex networking problems and contributing to security infrastructure that could eventually underpin critical systems around the world. And because this remains a relatively small, specialist engineering team, your contribution won't disappear into a huge development organisation. You'll see the impact of what you build. What the Director of Engineering Needs in This Role This is a tall order intentionally so. First and foremost, you must have genuine depth in network programming with C and C++. We're particularly interested in engineers with strong working knowledge of Layer 3 OSI protocols, low-level packet analysis and routing, OSPF, TAP/TUN devices and UDP tunnelling, UDP hole punching and STUN technologies, IPTables and packet routing strategies, code threading and multitasking, IPC and shared-memory communication, and Linux kernel-level development. You'll ideally also be comfortable with several of the following areas: compilers and static libraries, cross-compiling and porting across iOS, Android, Windows and Linux, containerised microservices using Docker and Kubernetes, CI/CD and GitLab environments, distributed cloud platforms including AWS, Azure and OVH, and development environments including VS Code, GitLab and Nexus. We don't expect one person to tick every box. What we do need is someone who can demonstrate a high level of competence in networking, packet routing and packet analysis, together with meaningful experience across at least three or four of the areas above. That networking foundation is important. Without it, the learning curve into the technology will simply be too steep. The Kind of Engineer Who Will Thrive Here You'll probably have 10+ years' experience designing, architecting and developing sophisticated C++ systems, although depth of expertise matters more than an arbitrary number. You'll be comfortable operating in Linux environments, including Debian, CentOS and embedded variants, and ideally understand symmetric and asymmetric cryptography, hashing and secure distributed systems. More importantly, you'll be someone who enjoys getting underneath a problem. Someone who wants to understand what is actually happening to the packet, rather than simply calling an abstraction several layers above it. You'll document clearly, automate where it makes sense, challenge assumptions constructively and be comfortable working in an environment where engineers are expected to think rather than simply execute tickets. Previous start-up, IoT, edge computing, GPU/AI or blockchain experience would be useful, but isn't essential. Why This Matters Nine years in, this is no longer an academic experiment. It isn't a concept. It isn't a slide deck. And it isn't another IoT start-up promising to change the world with an idea. There is patented technology, years of engineering behind it and a platform being prepared for much wider adoption. The next stage is about scale. The successful engineers won't simply be writing C++ code. They'll be helping determine how machines authenticate, communicate and establish trust across industrial systems, critical infrastructure and other highly secure environments. You'll receive a competitive base salary plus significant equity, reflecting the opportunity to join at a stage where your contribution can still materially influence both the technology and the company's future. The role is permanent and fully remote. If you're a serious low-level C++ engineer who understands packets, routing, tunnelling and network behaviour and the idea of taking technology from Oxford research roots towards global security infrastructure sounds more interesting than another conventional development role I'd like to hear from you. Edison Hill Search are operating and advertising as an Employment Agency for permanent positions and as an Employment Business for interim / contract / temporary positions. Edison Hill Search are an Equal Opportunities employer and we encourage applicants from all backgrounds.
Research Scientist/Engineer - Agent Systems & Reinforcement Learning Location: London Salary: (phone number removed) per annum + permanent benefits + bonus Job Type: Permanent, Full-Time, On-site About the Opportunity We are partnering with a leading AI research organisation focused on developing sustainable, generalisable and evolvable Agent systems that represent the next frontier of artificial intelligence. This team is exploring how autonomous AI agents can operate effectively across complex environments, continuously learn from experience, and improve their capabilities over extended periods of execution. This is an exceptional opportunity to join a world-class research environment working at the intersection of Agents, Large Language Models, Reinforcement Learning and Autonomous Systems , contributing to cutting-edge research that could play a significant role in advancing the path towards Artificial General Intelligence (AGI). You will work alongside internationally recognised researchers and engineers, with access to significant computational resources and the freedom to investigate ambitious research challenges while helping translate breakthrough ideas into practical AI systems. The Role As a key member of the research team, you will contribute to the design and development of next-generation Agent systems, focusing on long-term reasoning, memory, self-improvement and reinforcement learning-driven optimisation. Key Responsibilities Agent Memory & Long-Term Reasoning Design and develop advanced Agent memory architectures capable of supporting ultra-long context processing. Research techniques to mitigate memory degradation in long-running Agent environments. Improve information retrieval, storage and utilisation mechanisms to enhance long-term planning and decision-making. Explore scalable approaches for persistent memory systems across complex task environments. Agent Self-Evolution & Autonomous Learning Develop self-evolving Agent capabilities that enable continuous improvement through experience. Research unified Agent representations and optimisation frameworks to support autonomous adaptation. Build systems that facilitate iterative self-improvement and long-term learning. Contribute to the development of Agent Harness frameworks that enable scalable evolution of autonomous agents. Agentic Reinforcement Learning Investigate advanced reinforcement learning methodologies for Agent optimisation. Develop both parametric and non-parametric RL approaches to improve Agent performance. Build collaborative update pipelines connecting Agent policy models and Agent execution frameworks. Evaluate and improve learning efficiency across diverse environments and task domains. Research & Innovation Conduct novel research in Agent systems, Large Language Model reasoning and reinforcement learning. Publish findings and contribute to the broader AI research community. Collaborate with multidisciplinary teams to translate research breakthroughs into practical systems. Stay at the forefront of emerging developments within autonomous AI and intelligent agent technologies. About You Essential Requirements Bachelor's degree or higher in Computer Science, Artificial Intelligence, Mathematics, Statistics or a related technical discipline. Strong engineering implementation skills and/or deep theoretical foundations in machine learning and AI. Demonstrated expertise in at least one of the following areas: Agent Systems, Reinforcement Learning, Large Language Models, Autonomous AI or Reasoning Systems. Excellent programming skills, particularly in Python and modern machine learning frameworks. Strong analytical and problem-solving abilities with a passion for tackling complex research challenges. Excellent communication and collaboration skills within multidisciplinary research teams. Commitment to working within a highly ambitious and fast-paced research environment. First-author publications at leading conferences including NeurIPS, ICML, ICLR, ACL, EMNLP or equivalent. Desirable Requirements Experience conducting cutting-edge research in Agent systems, reinforcement learning or foundation models. High-impact research contributions, highly cited publications or influential open-source projects. Track record of success in relevant competitions such as Kaggle, ARC-AGI or similar AI benchmarks. Experience developing large-scale AI systems within industry, academia or advanced R&D environments.
01/09/2026
Full time
Research Scientist/Engineer - Agent Systems & Reinforcement Learning Location: London Salary: (phone number removed) per annum + permanent benefits + bonus Job Type: Permanent, Full-Time, On-site About the Opportunity We are partnering with a leading AI research organisation focused on developing sustainable, generalisable and evolvable Agent systems that represent the next frontier of artificial intelligence. This team is exploring how autonomous AI agents can operate effectively across complex environments, continuously learn from experience, and improve their capabilities over extended periods of execution. This is an exceptional opportunity to join a world-class research environment working at the intersection of Agents, Large Language Models, Reinforcement Learning and Autonomous Systems , contributing to cutting-edge research that could play a significant role in advancing the path towards Artificial General Intelligence (AGI). You will work alongside internationally recognised researchers and engineers, with access to significant computational resources and the freedom to investigate ambitious research challenges while helping translate breakthrough ideas into practical AI systems. The Role As a key member of the research team, you will contribute to the design and development of next-generation Agent systems, focusing on long-term reasoning, memory, self-improvement and reinforcement learning-driven optimisation. Key Responsibilities Agent Memory & Long-Term Reasoning Design and develop advanced Agent memory architectures capable of supporting ultra-long context processing. Research techniques to mitigate memory degradation in long-running Agent environments. Improve information retrieval, storage and utilisation mechanisms to enhance long-term planning and decision-making. Explore scalable approaches for persistent memory systems across complex task environments. Agent Self-Evolution & Autonomous Learning Develop self-evolving Agent capabilities that enable continuous improvement through experience. Research unified Agent representations and optimisation frameworks to support autonomous adaptation. Build systems that facilitate iterative self-improvement and long-term learning. Contribute to the development of Agent Harness frameworks that enable scalable evolution of autonomous agents. Agentic Reinforcement Learning Investigate advanced reinforcement learning methodologies for Agent optimisation. Develop both parametric and non-parametric RL approaches to improve Agent performance. Build collaborative update pipelines connecting Agent policy models and Agent execution frameworks. Evaluate and improve learning efficiency across diverse environments and task domains. Research & Innovation Conduct novel research in Agent systems, Large Language Model reasoning and reinforcement learning. Publish findings and contribute to the broader AI research community. Collaborate with multidisciplinary teams to translate research breakthroughs into practical systems. Stay at the forefront of emerging developments within autonomous AI and intelligent agent technologies. About You Essential Requirements Bachelor's degree or higher in Computer Science, Artificial Intelligence, Mathematics, Statistics or a related technical discipline. Strong engineering implementation skills and/or deep theoretical foundations in machine learning and AI. Demonstrated expertise in at least one of the following areas: Agent Systems, Reinforcement Learning, Large Language Models, Autonomous AI or Reasoning Systems. Excellent programming skills, particularly in Python and modern machine learning frameworks. Strong analytical and problem-solving abilities with a passion for tackling complex research challenges. Excellent communication and collaboration skills within multidisciplinary research teams. Commitment to working within a highly ambitious and fast-paced research environment. First-author publications at leading conferences including NeurIPS, ICML, ICLR, ACL, EMNLP or equivalent. Desirable Requirements Experience conducting cutting-edge research in Agent systems, reinforcement learning or foundation models. High-impact research contributions, highly cited publications or influential open-source projects. Track record of success in relevant competitions such as Kaggle, ARC-AGI or similar AI benchmarks. Experience developing large-scale AI systems within industry, academia or advanced R&D environments.
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. We are seeking a highly skilled Hybrid Algorithm Researcher to develop advanced algorithmic software for future products in Advanced Signal Processing (ASP) and Position, Navigation & Timing (PNT). This is a unique opportunity to work at the intersection of classical signal processing and AI-based methods, applying both to complex sensing, modelling, tracking, fusion, and estimation challenges in contested electromagnetic environments. This role is ideal for someone who thrives on solving difficult technical problems and enjoys turning novel research into practical, high-impact solutions. You will contribute to low-TRL research and development activities, helping to shape technologies that remain robust, adaptable, and effective in real-world and adversarial conditions. What you will do Lead the development of hybrid algorithmic software in C++, MATLAB, Mathematica, and Python. Design, adapt, and evaluate hybrid algorithms for sensor modelling, processing, data fusion, tracking, state estimation, and anomaly detection. Apply time- and frequency-domain methods, including Fourier analysis, digital sampling, and filter design. Review recent research and translate novel techniques into practical ASP/PNT solutions. Improve the robustness of traditional algorithms for challenging, real-world data and systems. Use machine learning where it adds value, particularly for non-linear dynamics and complex system behaviour. Support proposals, bids, and project delivery for research and development activities. Mentor junior engineers and help strengthen technical capability across the team. What we are looking for You will bring substantial recent experience in low-TRL research and development, ideally within ASP, PNT, sensor fusion, or a related field. You should be confident working across theory and implementation, and comfortable applying hybrid white-box and black-box approaches to real engineering problems. Essential experience Experience implementing hybrid algorithms that combine classical and ML-based approaches. Applied experience in one or more of the following: feature extraction, data fusion, target tracking, image segmentation, image matching, sensor calibration, state estimation, anomaly detection, integrity monitoring, system modelling, or synthetic data generation. Strong understanding of time and frequency domain methods, including Fourier transforms, digital sampling, and filter design. Ability to evaluate, adapt, and implement techniques from recent research papers. Experience making algorithms robust to real-world data and complex physical system behaviour. Practical coding experience in C++, MATLAB, Mathematica, and/or Python. Proven ability to work across research, development, technical leadership, and delivery. Desirable experience Knowledge of emerging sensing and PNT technologies, electronic warfare, radar, sonar, or related domains. Experience with EKF, UKF, Lie Group UKF, or physics-informed machine learning. Experience supporting bids, funding applications, or collaborative consortia. Exposure to contested electromagnetic environments and resilient sensing challenges. Experience mentoring engineers or acting in a technical leadership capacity. About you You are a technically curious problem-solver who enjoys working at the boundary between research and practical engineering. You are able to move confidently between mathematical reasoning, software development, and applied experimentation, and you know when to use classical methods, machine learning, or a combination of both. You communicate complex ideas clearly, work well across disciplines, and are motivated by difficult problems that have real operational value. You take pride in producing high-quality technical output and contributing to an innovative, collaborative environment. A Bachelors degree with honours, Masters degree, or PhD in a relevant discipline is expected, along with few years of recent experience in related research and development. Why join us This is an opportunity to work on technologies that support the next generation of resilient sensing and navigation capability. You will help develop solutions for challenging operational environments, contribute to future product concepts, and play a meaningful role in building technical depth across the team. The work is ambitious, collaborative, and highly impactful - ideal for someone looking to apply advanced algorithms to genuinely complex, real-world challenges. Benefits Performance-related bonus Half day every Friday, usually finishing around 13:00 28 days annual leave (plus bank holidays) with opportunity to buy up to 40 hours/year (pro rata) 24 hours volunteering paid for Private healthcare Pension scheme Life cover 24/7 Employee Assistance Program and access to mental wellbeing app Employee discount shopping schemes on major brands and retailers Gym membership discounts Security Clearance Requirement Due to the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires Security Clearance (SC). It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years' residence in the UK over the last 5 years may be accepted, with additional overseas checks. Please visit the UKSV website for further guidance: . At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here. If this role isn't quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here. Join Thales in the UK - Innovate with us and shape the future!
01/09/2026
Full time
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. We are seeking a highly skilled Hybrid Algorithm Researcher to develop advanced algorithmic software for future products in Advanced Signal Processing (ASP) and Position, Navigation & Timing (PNT). This is a unique opportunity to work at the intersection of classical signal processing and AI-based methods, applying both to complex sensing, modelling, tracking, fusion, and estimation challenges in contested electromagnetic environments. This role is ideal for someone who thrives on solving difficult technical problems and enjoys turning novel research into practical, high-impact solutions. You will contribute to low-TRL research and development activities, helping to shape technologies that remain robust, adaptable, and effective in real-world and adversarial conditions. What you will do Lead the development of hybrid algorithmic software in C++, MATLAB, Mathematica, and Python. Design, adapt, and evaluate hybrid algorithms for sensor modelling, processing, data fusion, tracking, state estimation, and anomaly detection. Apply time- and frequency-domain methods, including Fourier analysis, digital sampling, and filter design. Review recent research and translate novel techniques into practical ASP/PNT solutions. Improve the robustness of traditional algorithms for challenging, real-world data and systems. Use machine learning where it adds value, particularly for non-linear dynamics and complex system behaviour. Support proposals, bids, and project delivery for research and development activities. Mentor junior engineers and help strengthen technical capability across the team. What we are looking for You will bring substantial recent experience in low-TRL research and development, ideally within ASP, PNT, sensor fusion, or a related field. You should be confident working across theory and implementation, and comfortable applying hybrid white-box and black-box approaches to real engineering problems. Essential experience Experience implementing hybrid algorithms that combine classical and ML-based approaches. Applied experience in one or more of the following: feature extraction, data fusion, target tracking, image segmentation, image matching, sensor calibration, state estimation, anomaly detection, integrity monitoring, system modelling, or synthetic data generation. Strong understanding of time and frequency domain methods, including Fourier transforms, digital sampling, and filter design. Ability to evaluate, adapt, and implement techniques from recent research papers. Experience making algorithms robust to real-world data and complex physical system behaviour. Practical coding experience in C++, MATLAB, Mathematica, and/or Python. Proven ability to work across research, development, technical leadership, and delivery. Desirable experience Knowledge of emerging sensing and PNT technologies, electronic warfare, radar, sonar, or related domains. Experience with EKF, UKF, Lie Group UKF, or physics-informed machine learning. Experience supporting bids, funding applications, or collaborative consortia. Exposure to contested electromagnetic environments and resilient sensing challenges. Experience mentoring engineers or acting in a technical leadership capacity. About you You are a technically curious problem-solver who enjoys working at the boundary between research and practical engineering. You are able to move confidently between mathematical reasoning, software development, and applied experimentation, and you know when to use classical methods, machine learning, or a combination of both. You communicate complex ideas clearly, work well across disciplines, and are motivated by difficult problems that have real operational value. You take pride in producing high-quality technical output and contributing to an innovative, collaborative environment. A Bachelors degree with honours, Masters degree, or PhD in a relevant discipline is expected, along with few years of recent experience in related research and development. Why join us This is an opportunity to work on technologies that support the next generation of resilient sensing and navigation capability. You will help develop solutions for challenging operational environments, contribute to future product concepts, and play a meaningful role in building technical depth across the team. The work is ambitious, collaborative, and highly impactful - ideal for someone looking to apply advanced algorithms to genuinely complex, real-world challenges. Benefits Performance-related bonus Half day every Friday, usually finishing around 13:00 28 days annual leave (plus bank holidays) with opportunity to buy up to 40 hours/year (pro rata) 24 hours volunteering paid for Private healthcare Pension scheme Life cover 24/7 Employee Assistance Program and access to mental wellbeing app Employee discount shopping schemes on major brands and retailers Gym membership discounts Security Clearance Requirement Due to the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires Security Clearance (SC). It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years' residence in the UK over the last 5 years may be accepted, with additional overseas checks. Please visit the UKSV website for further guidance: . At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here. If this role isn't quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here. Join Thales in the UK - Innovate with us and shape the future!
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. AI Researcher Reading (RG2 6GF) - Hybrid Primary Purpose of the Role: To conduct high-impact AI research that develops novel, trustworthy and operationally relevant AI capabilities across Thales UK businesses and for our customers, increasing the quality of our offers, winning new business, strengthening technical differentiation, and improving customer outcomes. As part of the growing software, AI and research capability in cortAIx Factory / cortAIx UK, the AI Researcher will collaborate with AI engineers, AI assurance specialists, human-machine teaming researchers, product owners, domain experts, data engineers and software engineers to turn complex operational and business challenges into validated AI research outcomes, proofs of concept and transferable technical capability. The role will contribute novel AI methods, research assets, technical reports, publications, invention disclosures and reusable experimental approaches to Thales UK's internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used transversally throughout the business. We are interested in people with a background of both conduct research and delivering across a diverse range of products or industries. We are looking for those who can undertake the research but also understand how to translate this into product. Highly advantageous if you've supported or led bids/bid requirements. Key Responsibilities and Tasks: Conduct applied and experimental AI research to solve complex customer and business problems across defence, aerospace, cyber security, rail, critical national infrastructure and related domains. Develop state-of-the-art AI/ML solutions, proofs of concept and research prototypes using real-world data and operationally relevant problem statements. Investigate, design, implement and evaluate advanced AI methods, including but not limited to deep learning, multimodal AI, self-supervised learning, foundation models, generative AI, computer vision, NLP/LLMs, time-series analytics and reinforcement learning where relevant. Translate business and customer needs into clear research questions, experimental plans, technical requirements and measurable success criteria. Design robust evaluation methodologies, including baselines, benchmarks, ablation studies, uncertainty assessment, robustness testing and performance measurement against operationally meaningful metrics. Collaborate with AI V&V, AI Assurance, Human-Machine Teaming and Applied AI groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency, fairness, privacy, security and alignment with MOD, regulatory and Thales governance requirements. Create proofs of concept, publications, invention disclosures, patents, technical reports and reusable research assets around advanced AI topics such as multimodal learning, self-supervised learning, foundation models and human-AI collaboration. Package research outputs in a form that enables transition to AI engineering teams, including demonstrator code, model cards, experiment reports, design notes and handover documentation. Support bids, PoCs, demos, customer workshops, innovation campaigns and stakeholder briefings by communicating research concepts and outcomes to technical and non-technical audiences. Work with data engineers, architects and domain experts on data acquisition, labelling strategies, synthetic data approaches, integration of third-party data and data quality management. Horizon scan for major AI research and technology trends, assess relevance to Thales markets, run trials and share best practices to accelerate responsible adoption. Skills, experience and qualifications required Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience. Relevant subject areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Engineering, Physics or a related technical discipline. Strong Python programming skills; proficiency with modern software engineering and research practices, including testing, code quality, reproducibility and collaborative development. Experience conducting AI/ML research or advanced AI development in complex technical environments, preferably including defence, aviation, rail, cyber security, safety-critical, mission-critical or similarly regulated domains. Expertise in ML/DL algorithms and techniques for supervised, unsupervised, self-supervised and, where relevant, reinforcement learning. Proven ability to take AI research from problem framing through experimental design, model development, evaluation and prototype demonstration. Hands-on experience in at least one advanced AI area such as deep neural networks, computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial robustness and secure AI. Scientific and technical writing skills, including preparation of technical reports, research papers, invention disclosures, model cards and experiment reports. Demonstrable experience producing high-quality technical documentation, research outputs, model evaluations or stakeholder briefings. Interpersonal Skills Ability to engage and influence diverse stakeholders, including Product Engineering Leaders, Customers, Design Authorities, Project Management, IS/IT, research partners and academic collaborators. Highly effective in a matrix-based organisation; a collaborative team player who drives outcomes while maintaining scientific rigour. Excellent communication skills; able to explain complex AI research concepts clearly to technical and non-technical audiences. Curious, creative and intellectually rigorous, with the ability to challenge constructively and develop novel solutions to ambiguous problems. Encourages an open environment where ideas are shared, technical debate is welcomed and innovation thrives. Desirable PhD or equivalent research experience in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Engineering, Physics or a related discipline. Peer-reviewed publications, patents, invention disclosures, open-source contributions or recognised technical innovations. Experience with governance of architecture, research designs or detailed technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids, proposals, customer demonstrations or externally funded innovation activities. Knowledge of cloud AI services, HPC environments, containerisation and secure research environments is desirable. Security Clearance statement Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to be a sole British National and achieve Security Clearance (SC) without any caveats. It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances . click apply for full job details
01/09/2026
Full time
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. AI Researcher Reading (RG2 6GF) - Hybrid Primary Purpose of the Role: To conduct high-impact AI research that develops novel, trustworthy and operationally relevant AI capabilities across Thales UK businesses and for our customers, increasing the quality of our offers, winning new business, strengthening technical differentiation, and improving customer outcomes. As part of the growing software, AI and research capability in cortAIx Factory / cortAIx UK, the AI Researcher will collaborate with AI engineers, AI assurance specialists, human-machine teaming researchers, product owners, domain experts, data engineers and software engineers to turn complex operational and business challenges into validated AI research outcomes, proofs of concept and transferable technical capability. The role will contribute novel AI methods, research assets, technical reports, publications, invention disclosures and reusable experimental approaches to Thales UK's internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used transversally throughout the business. We are interested in people with a background of both conduct research and delivering across a diverse range of products or industries. We are looking for those who can undertake the research but also understand how to translate this into product. Highly advantageous if you've supported or led bids/bid requirements. Key Responsibilities and Tasks: Conduct applied and experimental AI research to solve complex customer and business problems across defence, aerospace, cyber security, rail, critical national infrastructure and related domains. Develop state-of-the-art AI/ML solutions, proofs of concept and research prototypes using real-world data and operationally relevant problem statements. Investigate, design, implement and evaluate advanced AI methods, including but not limited to deep learning, multimodal AI, self-supervised learning, foundation models, generative AI, computer vision, NLP/LLMs, time-series analytics and reinforcement learning where relevant. Translate business and customer needs into clear research questions, experimental plans, technical requirements and measurable success criteria. Design robust evaluation methodologies, including baselines, benchmarks, ablation studies, uncertainty assessment, robustness testing and performance measurement against operationally meaningful metrics. Collaborate with AI V&V, AI Assurance, Human-Machine Teaming and Applied AI groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency, fairness, privacy, security and alignment with MOD, regulatory and Thales governance requirements. Create proofs of concept, publications, invention disclosures, patents, technical reports and reusable research assets around advanced AI topics such as multimodal learning, self-supervised learning, foundation models and human-AI collaboration. Package research outputs in a form that enables transition to AI engineering teams, including demonstrator code, model cards, experiment reports, design notes and handover documentation. Support bids, PoCs, demos, customer workshops, innovation campaigns and stakeholder briefings by communicating research concepts and outcomes to technical and non-technical audiences. Work with data engineers, architects and domain experts on data acquisition, labelling strategies, synthetic data approaches, integration of third-party data and data quality management. Horizon scan for major AI research and technology trends, assess relevance to Thales markets, run trials and share best practices to accelerate responsible adoption. Skills, experience and qualifications required Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience. Relevant subject areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Engineering, Physics or a related technical discipline. Strong Python programming skills; proficiency with modern software engineering and research practices, including testing, code quality, reproducibility and collaborative development. Experience conducting AI/ML research or advanced AI development in complex technical environments, preferably including defence, aviation, rail, cyber security, safety-critical, mission-critical or similarly regulated domains. Expertise in ML/DL algorithms and techniques for supervised, unsupervised, self-supervised and, where relevant, reinforcement learning. Proven ability to take AI research from problem framing through experimental design, model development, evaluation and prototype demonstration. Hands-on experience in at least one advanced AI area such as deep neural networks, computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial robustness and secure AI. Scientific and technical writing skills, including preparation of technical reports, research papers, invention disclosures, model cards and experiment reports. Demonstrable experience producing high-quality technical documentation, research outputs, model evaluations or stakeholder briefings. Interpersonal Skills Ability to engage and influence diverse stakeholders, including Product Engineering Leaders, Customers, Design Authorities, Project Management, IS/IT, research partners and academic collaborators. Highly effective in a matrix-based organisation; a collaborative team player who drives outcomes while maintaining scientific rigour. Excellent communication skills; able to explain complex AI research concepts clearly to technical and non-technical audiences. Curious, creative and intellectually rigorous, with the ability to challenge constructively and develop novel solutions to ambiguous problems. Encourages an open environment where ideas are shared, technical debate is welcomed and innovation thrives. Desirable PhD or equivalent research experience in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Engineering, Physics or a related discipline. Peer-reviewed publications, patents, invention disclosures, open-source contributions or recognised technical innovations. Experience with governance of architecture, research designs or detailed technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids, proposals, customer demonstrations or externally funded innovation activities. Knowledge of cloud AI services, HPC environments, containerisation and secure research environments is desirable. Security Clearance statement Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to be a sole British National and achieve Security Clearance (SC) without any caveats. It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances . click apply for full job details
